Do you know how complicated the climate is? Look for hidden patterns

 Mention climate, may immediately think of wind, rain and other weather phenomena. In fact, the connotation of weather and climate is different, weather is only one aspect of climate. Although we feel that weather forecasts are fairly accurate at the moment, it is very difficult to predict climate change accurately because climate is a complex system with many variables.

However, there are people who persist in the most difficult things. Such is the case with JapanEse-American meteorologist Shukiro Maki (left) and German meteorologist Klaus Hasselmann (center), who won the 2021 Nobel Prize in Physics for tackling part of the puzzle of long-term climate prediction. Along with them, Italian physicist Giorgio Parisi (right) won the prize. He studied the interaction between microdisorder and macroorder in complex systems and promoted the theoretical research and practical application of complex systems.

Carbon dioxide emissions are the main cause of global warming

As early as the first half of the 20th century, people realized that the average global temperature was gradually increasing, which is the problem of global warming. Later, scientists found that it was mainly caused by human activity emitting too much carbon dioxide, a greenhouse gas that can heat the atmosphere.

There are many factors affecting climate change. How can we prove that carbon dioxide is the main factor causing global warming? Maki and his colleague Richard Weiseld used physics to build a radiative convection balance tapir model that mimics the relationship between changes in atmospheric composition and temperature. The model clearly shows that the average global temperature will continue to rise as the concentration of carbon dioxide in the atmosphere rises. Using this model, Maki predicted the extent of future global warming: for every doubling of the concentration of carbon dioxide in the atmosphere, the average global temperature would rise by 2.3 degrees Celsius.

Maki also found that carbon dioxide flows through the atmosphere. Rising emissions of carbon dioxide suffer not just for the emitters, but for the whole world. Based on his model, Maki predicted that the polar regions would warm more than the rest of the world, a prediction later confirmed by observations of glaciers at the north and South Poles. Therefore, if energy conservation and emission reduction are not implemented, people will not only suffer more extreme weather due to global warming, but also lose their coastal habitats due to rising sea levels.

Human activity is responsible for global warming

There have been many great events of global warming or cooling in earth's history, many before humans even existed. Is the recent global warming event really caused by human activity? Hasselman's work helps clear up some of the doubts.

There are many factors affecting climate change, some of which have very different short-term and long-term effects. Although short-term weather forecasts are more accurate than long-term climate forecasts, short-term weather changes are more chaotic than long-term climate changes. So trying to find long-term patterns in short-term weather changes is like trying to find the direction of a twine in a tangle.

Hasselman found that changes in solar radiation, volcanic particles and greenhouse gas concentrations leave unique signals in weather systems that can be identified, and that this "fingerprinting" approach can also be applied to human impacts on weather systems. Hasselman used this identification method to create a stochastic climate model that innovatively found patterns in complex weather systems. Stochastic climate models show that the increase in global average temperature is not a natural event, but the result of human activities, mainly increased carbon dioxide emissions.

Hidden laws of random climate phenomena

While Messengo and Hasselman's work has led to an understanding of the workings of complex systems such as climate, Parisi's work has led to an understanding of the macroscopic properties of complex systems. Parisi used spin glass to discover the laws behind random phenomena, which greatly enriched the theoretical study of complex systems.

In 1980, Parisi discovered hidden patterns in disordered complex materials. The disordered material is spin glass, not ordinary glass, but a copper-iron alloy that takes on a glassy state under special conditions. The iron atoms in spin glass are randomly mixed into a crystal grid of copper atoms, and the spin of the iron atoms (somewhat like the spin of a planet) creates a magnetic field, which makes spin glass magnetic. The spin direction of iron atoms in spin glass is disorderly and random, but the magnetism of spin glass is specific and ordered.

Through the study of spin glass, Parisi put forward the profound theory of "duplicate symmetry breaking". Simply put, it enables people to understand and describe the laws behind the randomness of complex systems, and is one of Parisi's most important contributions to complex system theory.

It has very strong practical use

A study by three scientists shows that it is possible to find macroscopically ordered properties of a microscopically complex and disordered climate system using sound statistical methods. Such research is not just theoretical, but practical. For example, the weather forecast we see every day is the result of meteorologists modeling the chaotic movement of the atmosphere.

As we face more and more meteorological disasters such as high temperature and heat, heavy rain and flood, super typhoon and so on, we realize that climate change poses a great threat to human existence. When formulating climate policies, the government should not only rely on people's intuitive feelings, but also identify the root causes of climate change, so as to take targeted measures. Messengabe and Hasselman both showed a link between climate change and carbon dioxide emissions. Therefore, in recent years, governments of various countries and relevant ORGANIZATIONS of the United Nations are vigorously advocating "carbon peak" and "carbon neutrality".



Moroccan football team: "The most familiar stranger"

   When I was still in college ten years ago, I led a sightseeing group of more than 30 Moroccan students. Before meeting them, my general impression of the Moroccans was that they are from North Africa but closer to the Arab world. They have religious beliefs, are used to worship, and are inextricably linked with France.   When I saw the real person, I realized that the North Africans in front of me were actually a group of children playing with each other and having fun in time. They were about the same age as me at the time. I have all kinds of nicknames and nicknames. During the process of taking them to Badaling, the Summer Palace and Houhai, two classmates and I, together with more than 30 Moroccan students, realized "cultural integration" and "world unity" in the small group to some extent.   During the World Cup in Qatar, I was surprised to find that the little-known Morocco team, which was eliminated in the group stage of the last World Cup, after miraculou

Zeigarnik effect

  As a freelancer, you have to fight procrastination every day. "I've made up my mind many times, but I just can't change it. Is it because I'm slow or slow?". In fact, many procrastinations are irrational. Many obstructions are imagined by myself. So distract, postpone, avoid confrontation. It's cool to procrastinate, and it's cool to procrastinate all the time, so I can't do it. Concentration is also related to physical strength. When the physical strength is exhausted, it is even more difficult to concentrate. You’ll tell yourself: I’m too tired to do this—okay, another perfect procrastination.   In 1927, Bruma Zeigarnik's senior research found that people are more likely to care about unfinished and interrupted work than completed work. This is the Zeigarnik effect. For example, we often don't care much about what we have got, but we will especially cherish what we have worked hard but haven't got. Therefore, the TV series will tell you

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